Biosecurity indemnification and attitudes of United States swine producers towards the prevention of an african swine fever outbreak.

Animal disease outbreaks, such as the recent outbreak of African Swine Fever in 2018, are a major concern for stakeholders across the food supply chain due to their potential to disrupt global food security, cause economic losses, and threaten animal welfare. As a result of their transboundary nature, discussions have shifted to preventive measures aimed at protecting livestock while ensuring food security and safety. Emergency assistance has been a critical response option during pandemics. However, this may not be sustainable in the long run because the expectation of government bailout may encourage risk taking behaviours. Our hypothesis is that an indemnity policy that is conditioned on showing biosecurity practices would increase compliance and reduce government expenditure during disease outbreaks. We developed and launched a survey from March to July 2022 targeted at swine producers across the US. From the survey, we examined livestock farmers' attitudes and intentions regarding biosecurity investment and assessed their attitudes towards the purchase of livestock insurance and reporting suspected infected livestock on their farm. We used a partial proportion odds model analysis to examine the model. Our analysis revealed that intention to call a veterinarian, trust in government agencies and risk perception of farmers were instrumental in the willingness to self-invest in biosecurity, purchase livestock insurance, and promptly report infected livestock on their farms. This provides evidence that biosecurity compliance would increase if indemnification was tied to a demonstration of effort to adopt biosecurity practices. We also show that individuals who have been in the industry for a longer period may become complacent and less likely to report outbreaks. Farmers with a higher share of income from their production operations bear a greater risk from their operational income and are more willing to report any suspected infections on their farms. The data suggest that motivating the willingness of farmers to invest in biosecurity while overcoming cost concerns is achievable.

Engagement in water governance action situations in the Lake Champlain Basin.

Water quality governance encompasses multiple "wicked" interacting problems that manifest within social-ecological systems. Concerned governments, institutions, and actors concerned with addressing these issues must wrestle with complex systems that span time, space, and scale. This complexity of connected systems requires the participation of multiple actors across political boundaries, problem areas, and hydrologic domains. In Lake Champlain (US), frequent cyanobacteria blooms negatively affect property values, recreational activities, and public infrastructure, in addition to their impacts on the aquatic ecosystem. Through a survey of actors working on water quality in the Lake Champlain Basin, we analyze how actor participation in structured issue forums creates a network of connected action situations across multiple spatial scales and problem domains. We apply exponential random graph models to quantify the effects of scale, issues, and homophily on actor participation in these forums. Our findings show that actors tend to favor participating in similarly scoped forums at their spatial scale, that actors are less likely to participate in structured forums focused on agriculture, and that actors participate independently of others with whom they have pre-existing collaborative relationships. Further, we find that in the case of the Lake Champlain Basin, actor participation in issues related to water quality is misaligned with modeled sources of nutrient pollution. This study demonstrates that the design and maintenance of water quality action situations play an important role in attracting the participation of actors working collaboratively to address wicked social-ecological problems. Further, linking current and potential configurations of governance networks to social-ecological outcomes can aid in the effective and efficient achievement of management objectives.

Effects of message delivery on cross-cultural biosecurity compliance: Insights from experimental simulations.

Background: Effective biosecurity communication of transmission risks and associated protective behaviors can reduce the impacts of infectious diseases in US animal agriculture. Yet, more than 1/5 of animal production workers speak a language other than English at home, and more than 40 percent are less than fluent in English. Communicating with these workers often involves translating into their primary languages. However, communication strategies targeting different cultural groups are not well-understood. Aims: To identify cross-linguistic risk communication strategies to facilitate compliance, we hypothesized that uncertainty avoidance cultures associated with the languages might affect biosecurity compliance contingent upon two additional covariates: (1) the risk of acquiring an infection and (2) the delivery method of the infection risk. Methods: We designed an experimental game simulating a line of separation (LOS) biosecurity tactic in a swine production facility, where participants were tasked with completing tasks inside and outside of the facility. Data were collected using games in the two most spoken languages in the US: English (EN) and Spanish (SP). Participants made binary decisions about whether to use the LOS biosecurity tactic based on the risk information provided. Mixed-effect logistic models were used to test the effects of covariates on using the LOS tactic by different language groups. Results: We found that biosecurity compliance rates of participants who took the experiments in the language associated with high and low uncertainty cultures showed no significant differences. However, there are substantial differences in how risk information is perceived between the two language groups under different infection risks. Specifically, and counterintuitively, SP participants were more risk-averse in gain scenarios but more risk-taking in loss scenarios. These differences are most pronounced in numeric risk messaging, indicating that numbers may not be the best way to communicate risk information regarding biosecurity cross-culturally. Conclusions: When confronted with situational biosecurity decisions, risk perception and preferences vary by language group. Effective biosecurity communication needs to account for these differences and not assume that direct translation of risk messages will result in comparable compliance.

Assessing strategic, tactical, and operational decision-making and risk in a livestock production chain through experimental simulation platforms.

This paper provides a research summary of a series of serious games and simulations that form the basis of an experimental platform for the study of human decision-making and behavior associated with biosecurity across complex livestock production chains. This platform is the first of its kind to address the challenges associated with scaling micro-behavior of biosecurity decision-making to macro-patterns of disease spread across strategic, tactical and operational levels, capturing the roles that facility managers and front-line workers play in making biosecurity decisions under risk and uncertainty. Informational and incentive treatments are tested within each game and simulation. Behavioral theories are used to explain these findings. Results from serious games in the form of behavioral probability distributions are then used to simulate disease incidence and spread across a complex production chain, demonstrating how micro-level behaviors contribute to larger macro-level patterns. In the case of this study, the propensity to adopt micro-level biosecurity practices are applied to a network percolation disease spread model. By presenting the suite of companion models of behavior and disease spread we are able to capture scaling dynamics of complex systems, and in the process, better understand how individual behaviors impact whole systems.

Comparing behavioral risk assessment strategies for quantifying biosecurity compliance to mitigate animal disease spread.

Understanding the impact of human behavior on the spread of disease is critical in mitigating outbreak severity. We designed an experimental game that emulated worker decision-making in a swine facility during an outbreak. In order to combat contamination, the simulation features a line-of-separation biosecurity protocol. Participants are provided disease severity information and can choose whether or not to comply with a shower protocol. Each simulated decision carried the potential for either an economic cost or an opportunity cost, both of which affected their potential real-world earnings. Participants must weigh the risk infection vs. an opportunity cost associated with compliance. Participants then completed a multiple price list (MPL) risk assessment survey. The survey uses a context-free, paired-lottery approach in which one of two options may be selected, with varying probabilities of a high and low risk payouts. We compared game response data to MPL risk assessment. Game risk was calculated using the normalized frequency of biosecurity compliance. Three predominant strategies were identified: risk averse participants who had the highest rate of compliance; risk tolerant participants who had the lowest compliance rate; and opportunists who adapted their strategy depending on disease risk. These findings were compared to the proportion of risk averse choices observed within the MPL and were classified into 3 categories: risk averse, risk tolerant and neutral. We found weak positive correlation between risk measured in our experimental game compared to the MPL. However, risk averse classified participants in the MPL tended to comply with the biosecurity protocol more often than those classified as risk tolerant. We also found that the behavioral risk clusters and categorization via the MPL were significantly, yet weakly associated. Overall, behavioral distributions were skewed toward more risk averse choices in both the MPL and game. However, the MPL risk assessment wasn't a strong predictor for observed game behavior. This may indicate that MPL risk aversion metrics might not be sufficient to capture these simulated, situational risk aversion behaviors. Experimental games have a large potential for expanding upon traditional survey instruments by immersing participants in a complex decision mechanism, and capturing dynamic and evolving behavioral signals.

Connecting livestock disease dynamics to human learning and biosecurity decisions.

The acceleration of animal disease spread worldwide due to increased animal, feed, and human movement has driven a growing body of epidemiological research as well as a deeper interest in human behavioral studies aimed at understanding their interconnectedness. Biosecurity measures can reduce the risk of infection, but human risk tolerance can hinder biosecurity investments and compliance. Humans may learn from hardship and become more risk averse, but sometimes they instead become more risk tolerant because they forget negative experiences happened in the past or because they come to believe they are immune. We represent the complexity of the hog production system with disease threats, human decision making, and human risk attitude using an agent-based model. Our objective is to explore the role of risk tolerant behaviors and the consequences of delayed biosecurity investments. We set up experiment with Monte Carlo simulations of scenarios designed with different risk tolerance amongst the swine producers and we derive distributions and trends of biosecurity and porcine epidemic diarrhea virus (PEDv) incidence emerging in the system. The output data allowed us to examine interactions between modes of risk tolerance and timings of biosecurity response discussing consequences for disease protection in the production system. The results show that hasty and delayed biosecurity responses or slow shifts toward a biosecure culture do not guarantee control of contamination when the disease has already spread in the system. In an effort to support effective disease prevention, our model results can inform policy making to move toward more resilient and healthy production systems. The modeled dynamics of risk attitude have also the potential to improve communication strategies for nudging and establishing risk averse behaviors thereby equipping the production system in case of foreign disease incursions.

Message Delivery Strategy Influences Willingness to Comply With Biosecurity.

As the Covid-19 pandemic continues worldwide, it has become increasingly clear that effective communication of disease transmission risks associated with protective behaviors is essential, and that communication tactics are not ubiquitously and homogenously understood. Analogous to Covid-19, communicable diseases in the hog industry result in millions of animal deaths and in the United States costs hundreds of millions of dollars annually. Protective behaviors such as preventative biosecurity practices are implemented to reduce these costs. Yet even with the knowledge of the importance of biosecurity, these practices are not employed consistently. The efficacy of biosecurity practices relies on consistent implementation and is influenced by a variety of behavioral factors under the umbrella of human decision-making. Using an experimental game, we collected data to quantify how different messages that described the likelihood of a disease incursion would influence willingness to follow biosecurity practices. Here we show that graphical messages combined with linguistic phrases demarking infection risk levels are more effective for ensuring compliance with biosecurity practices, as contrasted with either simple linguistic phrases or graphical messages with numeric demarcation of risk levels. All three of these delivery methods appear to be more effective than using a simple numeric value to describe probability of infection. Situationally, we saw greater than a 3-fold increase in compliance by shifting message strategy without changing the infection risk, highlighting the importance of situational awareness and context when designing messages.

Social-psychological determinants of farmer intention to adopt nutrient best management practices: Implications for resilient adaptation to climate change.

Successful adaptation to global climate change and enhancement of agricultural watersheds' resilience requires widespread use of Nutrient Best Management Practices (NBMPs) by farms of all sizes. In the US, adoption of many NBMP practices is voluntary and insufficient to achieve local and downstream conservation objectives. Despite evidence that both social-psychological factors and socio-economic factors influence farmer decision-making, very few studies of farmers' decision-making related to NBMP adoption combine these two factor groups in a theoretically rigorous way. To better understand farmers' management decisions, we test the social-psychological Theory of Planned Behavior (TPB) to determine the relative influence of attitudes, perceived social norms, and perceived behavioral control on adoption of nine NBMPs. A survey was designed by the research team and implemented by the U.S. Department of Agriculture-National Agricultural Statistics Service (USDA-NASS) in 2013, and replicated in 2016, on a stratified sample of 129 farmers (including panel data on 56 farmers). Farmers were located in the Missisquoi, and Lamoille River watersheds of the Lake Champlain Basin in the Northeast region of the United States. Survey responses revealed variation in past adoption of NBMPs was sensitive to practice type and farm size. We developed nine weighted structural equation models to test endogenous (social-psychological) and exogenous (policy, economic and demographic) predictors of farmer intention to adopt NBMPs. We found that perceived behavioral control had the largest effect size and strongest statistical significance on the farmers' expressed intentions to adopt NBMPs in the future. For a subset of NBMPs, perceived social norms and farmer attitudes toward these NBMPs were each also significant drivers of intention to adopt individual practices. Among the exogenous variables, we found that large farm size, college education, and having a conservation easement all had a positive influence on farmers' intention to adopt NBMPs. This study suggests that for widespread adoption of NBMPs, environmental managers, policy makers, and program developers should be attentive to farmers' perceived behavioral control, and support the design and execution of outreach and technical assistance programs that build on drivers of farmers' decision making.

Effects of Social Cues on Biosecurity Compliance in Livestock Facilities: Evidence From Experimental Simulations.

Disease outbreaks in U.S. animal livestock industries have economic impacts measured in hundreds of millions of dollars per year. Biosecurity, or procedures intended to protect animals against disease, is known to be effective at reducing infection risk at facilities. Yet, to the detriment of animal health, humans do not always follow biosecurity protocols. Human behavioral factors have been shown to influence willingness to follow biosecurity protocols. Here we show how social cues may affect cooperation with a biosecurity practice. Participants were immersed in a simulated swine production facility through a graphical user interface and prompted to make a decision that addressed their willingness to comply with a biosecurity practice. We tested the effect of varying three experimental variables: (1) the risk of acquiring an infection, (2) the delivery method of the infection risk information (numerical vs. graphical), and (3) the behavior of an automated coworker in the facility. We provide evidence that participants changed their behavior when they observed a simulated worker making a choice to follow or not follow a biosecurity protocol, even though the simulated worker had no economic effect on the participants' payouts. These results advance the understanding of human behavioral effects on biosecurity protocol decisions, demonstrating that social cues need to be considered by livestock facility managers when developing policies to make agricultural systems more disease resilient.

Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management.

Failing to mitigate propagation of disease spread can result in dire economic consequences for agricultural networks. Pathogens like Porcine Epidemic Diarrhea virus, can quickly spread among producers. Biosecurity is designed to prevent infection transmission. When considering biosecurity investments, management must balance the cost of protection versus the consequences of contracting an infection. Thus, an examination of the decision making processes associated with investment in biosecurity is important for enhancing system wide biosecurity. Data gathered from experimental gaming simulations can provide insights into behavioral strategies and inform the development of decision support systems. We created an online digital experiment to simulate outbreak scenarios among swine production supply chains, where participants were tasked with making biosecurity investment decisions. In Experiment One, we quantified the risk associated with each participant's decisions and delineated three dominant categories of risk attitudes: risk averse, risk tolerant, and opportunistic. Each risk class exhibited unique approaches in reaction to risk and disease information. We also tested how information uncertainty affects risk aversion, by varying the amount of visibility of the infection as well as the amount of biosecurity implemented across the system. We found evidence that more visibility in the number of infected sites increases risk averse behaviors, while more visibility in the amount of neighboring biosecurity increased risk taking behaviors. In Experiment Two, we were surprised to find no evidence for differences in behavior of livestock specialists compared to Amazon Mechanical Turk participants. Our findings provide support for using experimental gaming simulations to study how risk communication affects behavior, which can provide insights towards more effective messaging strategies.

Emulating Agricultural Disease Management: Comparing Risk Preferences Between Industry Professionals and Online Participants Using Experimental Gaming Simulations and Paired Lottery Choice Surveys.

Mitigating the spread of disease is crucial for the well-being of agricultural production systems. Implementing biosecurity disease prevention measures can be expensive, so producers must balance the costs of biosecurity investments with the expected benefits of reducing the risk of infections. To investigate the risk associated with this decision making process, we developed an online experimental game that simulates biosecurity investment allocation of a pork production facility during an outbreak. Participants are presented with several scenarios that vary the visibility of the disease status and biosecurity protection implemented at neighboring facilities. Certain rounds allowed participants to spend resources to reduce uncertainty and reveal neighboring biosecurity and/or disease status. We then test how this uncertainty affects the decisions to spend simulation dollars to increase biosecurity and reduce risk. We recruited 50 attendees from the 2018 World Pork Expo to participate in our simulation. We compared their performance to an opportunity sample of 50 online participants from the survey crowdsourcing tool, Amazon Mechanical Turk (MTurk). With respect to biosecurity investment, we did not find a significant difference between the risk behaviors of industry professionals and those of MTurk participants for each set of experimental scenarios. Notably, we found that our sample of industry professionals opted to pay to reveal disease and biosecurity information more often than MTurk participants. However, the biosecurity investment decisions were not significantly different during rounds in which additional information could be purchased. To further validate these findings, we compared the risk associated with each group's responses using a well-established risk assessment survey implementing paired lottery choices. Interestingly, we did not find a correlation in risk quantified with simulated biosecurity investment in comparison to the paired lottery choice survey. This may be evidence that general economic risk preferences may not always translate into simulated behavioral risk, perhaps due to the contextual immersion provided by experimental gaming simulations. Online recruitment tools can provide cost effective research quality data that can be rapidly assembled in comparison to industry professionals, who may be more challenging to sample at scale. Using a convenience sample of industry professionals for validation can also provide additional insights into the decision making process. These findings lend support to using online experimental simulations for interpreting risk associated with a complex decision mechanism.

Risk Attitudes Affect Livestock Biosecurity Decisions With Ramifications for Disease Control in a Simulated Production System.

Hog producers' operational decisions can be informed by an awareness of risks associated with emergent and endemic diseases. Outbreaks of porcine epidemic diarrhea virus (PEDv) have been re-occurring every year since the first onset in 2013 with substantial losses across the hog production supply chain. Interestingly, a decreasing trend in PEDv incidence is visible. We assert that changes in human behaviors may underlie this trend. Disease prevention using biosecurity practices is used to minimize risk of infection but its efficacy is conditional on human behavior and risk attitude. Standard epidemiological models bring important insights into disease dynamics but have limited predictive ability. Since research shows that human behavior plays a driving role in the disease spread process, the explicit inclusion of human behavior into models adds an important dimension to understanding disease spread. Here we analyze PEDv incidence emerging from an agent-based model (ABM) that uses both epidemiological dynamics and algorithms that incorporate heterogeneous human decisions. We investigate the effects of shifting fractions of hog producers between risk tolerant and risk averse positions. These shifts affect the dynamics describing willingness to increase biosecurity as a response to disease threats and, indirectly, change infection probabilities and the resultant intensity and impact of the disease outbreak. Our ABM generates empirically verifiable patterns of PEDv transmission. Scenario results show that relatively small shifts (10% of the producer agents) toward a risk averse position can lead to a significant decrease in total incidence. For significantly steeper decreases in disease incidence, the model's hog producer population needed at least 37.5% of risk averse. Our study provides insight into the link between risk attitude, decisions related to biosecurity, and consequent spread of disease within a livestock production system. We suggest that it is possible to create positive, lasting changes in animal health by nudging the population of livestock producers toward more risk averse behaviors. We make a case for integrating social and epidemiological aspects in disease spread models to test intervention strategies intended to improve biosecurity and animal health at the system scale.

Willingness to Comply With Biosecurity in Livestock Facilities: Evidence From Experimental Simulations.

Disease in U.S. animal livestock industries annually costs over a billion dollars. Adoption and compliance with biosecurity practices is necessary to successfully reduce the risk of disease introduction or spread. Yet, a variety of human behaviors, such as the urge to minimize time costs, may induce non-compliance with biosecurity practices. Utilizing a "serious gaming" approach, we examine how information about infection risk impacts compliance with biosecurity practices. We sought to understand how simulated environments affected compliance behavior with treatments that varied using three factors: (1) the risk of acquiring an infection, (2) the delivery method of the infection risk message (numerical, linguistic and graphical), and (3) the certainty of the infection risk information. Here we show that compliance is influenced by message delivery methodology, with numeric, linguistic, and graphical messages showing increasing efficacy, respectively. Moreover, increased situational uncertainty and increased risk were correlated with increases in compliance behavior. These results provide insight toward developing messages that are more effective and provide tools that will allow managers of livestock facilities and policy makers to nudge behavior toward more disease resilient systems via greater compliance with biosecurity practices.

Decision-making in livestock biosecurity practices amidst environmental and social uncertainty: Evidence from an experimental game.

Livestock industries are vulnerable to disease threats, which can cost billions of dollars and have substantial negative social ramifications. Losses are mitigated through increased use of disease-related biosecurity practices, making increased biosecurity an industry goal. Currently, there is no industry-wide standard for sharing information about disease incidence or on-site biosecurity strategies, resulting in uncertainty regarding disease prevalence and biosecurity strategies employed by industry stakeholders. Using an experimental simulation game, with primarily student participants, we examined willingness to invest in biosecurity when confronted with disease outbreak scenarios. We varied the scenarios by changing the information provided about 1) disease incidence and 2) biosecurity strategy or response by production facilities to the threat of disease. Here we show that willingness to invest in biosecurity increases with increased information about disease incidence, but decreases with increased information about biosecurity practices used by nearby facilities. Thus, the type or context of the uncertainty confronting the decision maker may be a major factor influencing behavior. Our findings suggest that policies and practices that encourage greater sharing of disease incidence information should have the greatest benefit for protecting herd health.

Universal Versus Targeted Screening for Lynch Syndrome: Comparing Ascertainment and Costs Based on Clinical Experience.

BACKGROUND: Strategies to screen colorectal cancers (CRCs) for Lynch syndrome are evolving rapidly; the optimal strategy remains uncertain. AIM: We compared targeted versus universal screening of CRCs for Lynch syndrome. METHODS: In 2010-2011, we employed targeted screening (age < 60 and/or Bethesda criteria). From 2012 to 2014, we screened all CRCs. Immunohistochemistry for the four mismatch repair proteins was done in all cases, followed by other diagnostic studies as indicated. We modeled the diagnostic costs of detecting Lynch syndrome and estimated the 5-year costs of preventing CRC by colonoscopy screening, using a system dynamics model. RESULTS: Using targeted screening, 51/175 (29 %) cancers fit criteria and were tested by immunohistochemistry; 15/51 (29 %, or 8.6 % of all CRCs) showed suspicious loss of ≥1 mismatch repair protein. Germline mismatch repair gene mutations were found in 4/4 cases sequenced (11 suspected cases did not have germline testing). Using universal screening, 17/292 (5.8 %) screened cancers had abnormal immunohistochemistry suspicious for Lynch syndrome. Germline mismatch repair mutations were found in only 3/10 cases sequenced (7 suspected cases did not have germline testing). The mean cost to identify Lynch syndrome probands was ~$23,333/case for targeted screening and ~$175,916/case for universal screening at our institution. Estimated costs to identify and screen probands and relatives were: targeted, $9798/case and universal, $38,452/case. CONCLUSIONS: In real-world Lynch syndrome management, incomplete clinical follow-up was the major barrier to do genetic testing. Targeted screening costs 2- to 7.5-fold less than universal and rarely misses Lynch syndrome cases. Future changes in testing costs will likely change the optimal algorithm.

Toward an Understanding of Citywide Urban Environmental Governance: An Examination of Stewardship Networks in Baltimore and Seattle.

Efforts to create more sustainable cities are evident in the proliferation of sustainability policies in cities worldwide. It has become widely proposed that the success of these urban sustainability initiatives will require city agencies to partner with, and even cede authority to, organizations from other sectors and levels of government. Yet the resulting collaborative networks are often poorly understood, and the study of large whole networks has been a challenge for researchers. We believe that a better understanding of citywide environmental governance networks can inform evaluations of their effectiveness, thus contributing to improved environmental management. Through two citywide surveys in Baltimore and Seattle, we collected data on the attributes of environmental stewardship organizations and their network relationships. We applied missing data treatment approaches and conducted social network and comparative analyses to examine (a) the organizational composition of the network, and (b) how information and knowledge are shared throughout the network. Findings revealed similarities in the number of actors and their distribution across sectors, but considerable variation in the types and locations of environmental stewardship activities, and in the number and distribution of network ties in the networks of each city. We discuss the results and potential implications of network research for urban sustainability governance.

System Dynamics Modeling Can be Leveraged to Predict Critical Care Pathways and Costs for End Stage Renal Disease: US Population to 2020.

Background: End Stage Renal Disease (ESRD) accounts for 9% of Medicare spending, with the beneficiaries suffering from ESRD costing 7-9 times more than the average. This population is expected to continue to grow as a portion of Medicare beneficiaries. To provide clinicians and administrators with a greater understanding of the combined costs associated with the multiple critical care pathways for End Stage Renal Disease we have developed a model to predict ESRD populations through 2020. Methods: A system dynamics model was designed to project the prevalence and total costs of ESRD treatment for the United States through 2020. Incidence, transplant and mortality rates were modeled for 35 age and primary diagnosis subgroups coursing through different ESRD critical care pathways. Using a web interface that allows users to alter certain combinations of parameters, several demonstration analysis were run to predict the impact of three policy interventions on the future of ESRD care Results: The model was successfully calibrated against the output of United States Renal Data System's (USRDS) prior predictions and tested by comparing the output to historical data. Our model predicts that the ESRD patient population will continue to rise, with total prevalence increasing to 829,000 by 2020. This would be a 30% increase from the reported 2010 prevalence. Conclusions: Findings suggest that clinical care and policy changes can be leveraged to more effectively and efficiently manage the inevitable growth of ESRD patient populations. Patients can be shifted to more effective treatments, while planning integrating systems thinking can save Medicare's ESRD program billions over the next decade.